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@napsternxg
Forked from pierre-haessig/logit_scale.ipynb
Last active August 29, 2015 14:27
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Logit scale, for plotting cumulated probability distributions (matplotlib implementation). Better visualization of the tails
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{
"metadata": {
"name": "",
"signature": "sha256:1f5e7082722e20d63021250818cf49fc5c4bf78a5b6f4d5d0abe7ddf0679f9e1"
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"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Logit plot scale for cumulative probability plot"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Example : samples from a Weibull distribution (fake wind measurements, see http://wind-data.ch/tools/weibull.php?lng=en for example)\n",
"\n",
"Other useful ressource on failure analysis with Weibull : https://www.wakari.io/nb/pybokeh/Weibull_Analysis\n",
"\n",
"Distribution info : http://en.wikipedia.org/wiki/Weibull_distribution\n",
"\n",
"* Cumulative distribution:\n",
"$F(x) = 1 - e^{-(x/\\lambda)^k}, \\quad x \\geq 0$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Pierre Haessig \u2014 April 2014"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"from scipy import stats"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 7
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"w_shape = 2.\n",
"w_scale = 6\n",
"#weib = stats.exponweib(a=w_shape, c=1, scale=w_scale) # doesn't work !\n",
"weib = stats.weibull_min(w_shape, scale=w_scale)\n",
"\n",
"vel = np.linspace(0, w_scale*3, 500)\n",
"\n",
"plt.plot(vel, weib.pdf(vel))\n",
"plt.title('Weibull pdf, scale={:.2f}, shape={:.2f}'.format(w_scale, w_shape))\n",
"plt.xlabel('wind speed (m/s)')\n",
"weib.mean()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 305,
"text": [
"5.3173615527165481"
]
},
{
"metadata": {},
"output_type": "display_data",
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efHw8derUiRo3bkydOnWic+fOqZVHV9RY7A8cOEDt2rUjR0dHWr58eYXHL1++TF26dKFG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\nAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0xaef3690>"
]
}
],
"prompt_number": 305
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Draw a samples from the Weibull distribution"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"N_samp = 200\n",
"vel_samp = weib.rvs(N_samp)\n",
"vel_samp.mean()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 74,
"text": [
"5.1082282289751495"
]
}
],
"prompt_number": 74
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"h_opts = dict(normed=True, alpha=1, histtype='stepfilled', color='#BBDDFF')\n",
"\n",
"plt.hist(vel_samp, bins = 15, cumulative=False, **h_opts)\n",
"plt.plot(vel, weib.pdf(vel), 'r')\n",
"plt.title('Weibull pdf, scale={:.2f}, shape={:.2f}'.format(w_scale, w_shape))\n",
"plt.xlabel('wind speed (m/s)');"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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DhoGvL3EDB3Lz5s0qeQQFBdGkSZMq9SGR1HYqGjvLHdkHBQWRmJhIUlISbm5u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\nT1RUFD4+PtjY2LBu3boy20okEomk+jH5HbQSiUQ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"text": [
"<matplotlib.figure.Figure at 0x9e17ad0>"
]
}
],
"prompt_number": 312
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"plt.hist(vel_samp, bins = 100, cumulative=True, **h_opts)\n",
"plt.plot(vel, weib.cdf(vel), 'r')\n",
"plt.title('Weibull cdf, scale={:.2f}, shape={:.2f}'.format(w_scale, w_shape))\n",
"plt.xlabel('wind speed (m/s)');"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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5+kyePJmuXbvi5ORESkoK33//femYKowKk+xsGn70CnZnj3Pih2DuO7kW/yCF\nQlF0UNdlGNj8+fNp2rQp+/fv5/r163Tv3p2zZ89ia2v7SN8ZM2ZgbW0NgK+vL+3atdN+Mj6oZZVl\nOyEhgYYNGxps/wW1HyyTxedB+8qVK9jb25fo9pOTk1nx5UpycnKws6sMwNmz57DJzqb2BxNIN7cg\nbPthNDa22lLLg6wzOzmWnPQELGs21Lb/vd4Q7QfLZPF52KU096fRaPKN8TbE8VQS7QfLDOmzf/9+\ndu7cCaCNl/pgIoQQha0MDg5mzpw5BAUFAbBgwQJMTU2ZNWuWtk+fPn2YPXs27dq1A+DZZ59l4cKF\ntGjRIv+OTEwoYlcGQcYLDWR0gtLxOnbsGEOGjWTQ+De1yxwS4pi+YxOpPQZy9b0l8K8bOz+MjBfV\nGKPT3Cn+zHh1Ev7+/jo/xpiO8ydF39hZZKbeokULwsLCiIiIwMnJie3bt7N169Z8fTw9PdmzZw/t\n2rXjzp07XLlyBXd398ezL2Nke/NATicoWa/lX6zgt52BJCYkUL2mM4PGvQaA7cXTNJ3Ul/CXZxM9\n5pVityNb8ATlpCvGcJwbiiKDupmZGStWrKBnz55oNBomTpyIl5cXq1atAmDKlCm89957jB8/Hl9f\nX3Jzc1m0aBFVi7hFmMK4+GLFl2zc9G2+ZWFXrzBw/Bt08mlBTRc3AOyP/UHj14Zz+T9fc7fnYAOY\nKhTlgyLLLyW6I1V+0QkZneDxvUaPeQHsatOqS1/tMlNTUzy8/TAzNweg+u878Hr/Jc4v305C2y46\nb9sYSx2Pgyq/6I6MXiVaflEoSgKnOh54+7UpcJ3z1tXU/WIupzf8TkojvzI2UyjKH0Yd1GX7RAY5\nnaB0vOqsWoTztlWc2nqQjDq6zX/+MLJlxKCcdMWYjvOyxqiDuqL0uHXrFpmZmaSkpBS4vu4Xn1Dz\nly2c3HaIrBpOZWynUJRfjPp2djLO8yCjE+jnde/ePVxdXenQqSsnQ0/j6FT7n5VC4L70A2rs3M6p\nrQeeKKDLOE2ActKN8nCcy4rK1BUlTlZWFvYO1dmwPzz/CiHwWDgLh8O7ObXlD7IdqhtGUKEoxxh1\nUJexfiajE5SAlxA0+M8bVDl5mFOb95FT5cmHvcpYK1ZOulFuj3MJMOqgrigjhKD+grexCz1K6Ld7\nyKlcxdBGCkW5xaiDuoxjUmV0At28Tp06RVBQ0CM/jtZb+gFVj+7Ny9BLMKAb45jwx0FGp6f5OJcd\no/6hVFEr6YHYAAAgAElEQVSybNz0LTt27ScquQKjX5sLgNuX86j+fz8RuvH/SqTkolAoisaoM3UZ\nP5FldALdvVp36cvg8dMBqL12KbV2bOTU1gOl8qOobNknKCddedqPc5kx6qCuKD2ct3yF66YvOLn1\nIFmOtQyto1AYDUZdfpFxTKqMTlC4l0ajoXfffrRt14Hvv/8eU9MK1PhtO3VXziP0272lenMLGcdf\nKyfdeNqO86cJlakrnojs7Gz2/t9uFn67F4A2yYk0fGciod/uIaP20zEFs0JRnjDqTF3G+pmMTvCo\n1/r166lRy4k6bnWpZGVN45YdeKaSFc3fmci5L38g1bNJqTvJWCtWTrrxtBznTyMqU1foRVZWFjk5\nOVy7do0OfUcydOJbVLK0wjI8jKYv9ufyvNUktupoaE2Fwmgx6kxdxvqZjE7wj5eziwtVHRxY+vnn\nONfxoFoNJ6rez8RvQi+uvz6Xuz0GlpmTjLVi5aQbsh/nTzMqU1foRXJyMj+dTsSiYiUAKqQk4zeh\nN7eGjOfmiMkGtlMoFEadqctYP5PRCQr2MsnJofFrw0nybU34K7PL3EnGWrFy0o2n6Th/2lCZuqJY\n7t27x4EDBwDI1WjyFgpBw7mvAnBlzgowMTGUnkKheAijDuoyzvMgo9PmzZvZEfArJhUr023AKMzM\nLai97nPsTh3h5PbDCDPDHEYyzmminHRDxuMc5PXSB6MO6oqi2bZtG5GRkRw6dAhvv2cY8srHAFTf\n/TO11y7hxA/H0NhWNrClQqF4GFVTlwyZnF6f/gZHzkVg5eRFw9Y9ALA9dxKv2ZM5+3UA9x++o5EB\nkC37BOWkKzId5w8jq5c+qExdkY8///yTxZ8tBSApKZHnp32Aw99zt1S8GYnvSwO4PO8bUpq0MKSm\nQqEoBKPO1GUck2pop+PHj3M89DyV67bg9f+spmr1mgDk3L1B0ykDiBz/RpmORS8KGcdfKyfdMPRx\nXhiyeumDytQVAEx/4y1OnznD7du3qNe4DX1HvvjPSiFwW72Y1AaNiZz0luEkFQpFsRh1UJexfmYo\np52BgQyYMANHpzrUrueZb12dVQtxPBnCqa0HpBq6KGOtWDnphoznHsjrpQ9GHdQV+fHya0sdD698\nyxz+2Inrpi84sSOE3EqWBjJTKBS6omrqklGWTkeOHMG2cmVsbG0Jvx5GJUurfOutrv9Jo5njOb/i\nB1KtzMvMS1dkrBUrJ92Q8dwDeb30odigHhQUhKenJ/Xr12fhwoUF9tm/fz9+fn74+PjQuXPnknZU\nlDAZGRncuXOHa9eu0bhFe747cpOfzyZTw7mOto9ZciK+UwZwbcYCkpq1NaCtQqHQhyLLLxqNhmnT\nprFnzx6cnZ1p2bIl/v7+eHn98xU9MTGRV155hd9//x0XFxfi4uJKXbqkkLF+VhZOvfr05czp05ib\nW9DF/3msbGzzd9Bo8Jn+PPHte3Bz2ERAzrqsctINGZ1kPPdAXi99KDKoh4SE4OHhgZubGwAjRowg\nICAgX1D/7rvvGDJkCC4uLgBUq1at9GwVJUJ6egafrAnEu5AMvN7nH2CamcHV2UvL2EyhUDwpRZZf\nYmJicHX95x6TLi4uxMTE5OsTFhZGfHw8Xbp0oUWLFnz77belY1oKyFg/Ky2nrKwsAgMD+fXXX0lI\niC+0X7U9v1Dr582c/+J7hPk/dXQZ67LKSTdkdJLx3AN5vfShyEzdRIfha9nZ2YSGhrJ3717S09Np\n27Ytbdq0oX79+o/0nTFjBtbW1gD4+vrSrl077dedBy9mWbYTEhIMuv+C2g8o6e0fPHiQj+bOpWJl\nR5zcvXF0sMs30VN2ciwWd2LwfncSZ1b/Qrq5gIfW56QnAOTrb+h2TnqCVD4PI4tPWbU1Gk2+ybCK\nOx4TEhKKXF/ezj992vv372fnzp0A2nipDyZCCFHYyuDgYObMmUNQUBAACxYswNTUlFmzZmn7LFy4\nkIyMDObMmQPApEmT6NWrF0OHDs2/IxMTitiVopQ5ePAg02e+z6LvDha43jQzg5ZD2xIzbBLRY6eV\nsZ3iaWbuFH9mvDoJf39/Q6uUS/SNnUWWX1q0aEFYWBgRERFkZWWxffv2R964AQMGcPjwYTQaDenp\n6Rw/fhxvb+/Hs1eUOL/9tpP33/+ANWvWFNmv4ZxppNXzInrMK2VkplAoSoMig7qZmRkrVqygZ8+e\neHt7M3z4cLy8vFi1ahWrVq0CwNPTk169etGkSRNat27N5MmTn5qgLmP9rKSdlq/4kuCLEZg61Gfw\npJkF9nH6fi12p49xef43hV4xKmNdVjnphoxOMp57IK+XPhR7RWnv3r3p3bt3vmVTpkzJ13777bd5\n++23S9ZMUWJ06TeS1l36FLjO9kIoHovf4eS2Q2isbcrYTKFQlDRGfUWpjGNSy9LJLDGextOG8uec\nL0n/13wv/0bGsc7KSTdkdJLx3AN5vfTBqIN6eeX27du0aduOZi1aEXz0CBUKut2cEDSaOY64Z/2J\n7Tus7CUVCkWpYNRBXcb6WUk4xcbGcvP2HSbMXsGCTXvxa9v1kT6uG5Zhcfc2YbMW6bRNGeuyykk3\nZHSS8dwDeb30Qc3SWE6pZGmFp2+rAtfZnjtJ3ZXzOfFjMMLCoozNFApFaWLUmbqM9bPSdqqQkkTj\n14fz59wvyajtrvPjZKzLKifdkNFJxnMP5PXSB6MO6kaHEHi99yLx7XsQ2+c5Q9soFIpSwKiDuoz1\nsydxunv3LiEhIZw/f77A9c7bvsH6rz8fa6IuGeuyykk3ZHSS8dwDeb30QdXUyxHT33iLg4ePYGfv\ngE+rTvnWWV85T72lszm57ZC6g5FCUY4x6qAuY/3sSZyyc3IYM/0Tuvo/n2+5aXoaTV4dRti7S4od\nj14YMtZllZNuyOgk47kH8nrpg1GXX4wFz7mvktSkFbcGjzW0ikKhKGWMOqjLWD8raaeaP2/GLvQo\nV+Z++UTbkbEuq5x0Q0YnGc89kNdLH4y6/FLesbxxnQbz3iB00x41r4tCYSQYdVCXsX6mr1NGRgbT\nXnud+5n3OR58DI82/QAwycmh0VujCX/5fVK9fJ/YS8a6rHLSDRmdZDz3QF4vfTDq8kt54O7du/zw\nww84NenKiGlzadkpb0bNul/+B41NZaJeeNXAhgqFoiwx6qAuY/3scZysrG3oMeQFug8ei62dPXah\nx3D+7msuLtoApiXzFstYl1VOuiGjk4znHsjrpQ9GHdSfZr5Y8SX1G3rRqUtXzMz/mb+lQmoKjd4a\nzZ+ffE2WYy0DGioUCkOgauqSoavTxUuXaN19KF38n8fWzl67vOHHr5HQpit3ewwsUS8Z67LKSTdk\ndJLx3AN5vfTBqIP600hmZibZ2dlkZ2Vh71qTOh5e2nWOu36gysnDHP/1tAENFQqFITHq8ouM9bOi\nnDIzM6lSpQo1azmxbds27KvV0K6reDuGhh+9woWlm0tl+KKMdVnlpBsyOsl47oG8XvqgMvWngNTU\nVMLCwkhLS6OCmTkB51Lyd8jNxXvGC0SPmUZy09aGkVQoFFJg1EFdxvpZQU6LFi3mq1WrcXCsiV/b\nLo+sr73+v1TIzCBi6rul5iVjXVY56YaMTjKeeyCvlz4YdVB/WsjJyaHf6GmMemX2I+tsLp/F7esF\nhOwIQRR0L1KFQmFUqJq6ZOjjZJqZgc8bowh7dwmZrnVL0UrOuqxy0g0ZnWQ890BeL31QqZ3ErFmz\nhri4OI4dO4pbs26PrPdY9A5p9b25NWiMAewUCoWMGHWmLmP97GGnKVOmcDo8nhoNW9Oma798/aoe\n/B3H3T9x+ZOvwcSk1L1krMsqJ92Q0UnGcw/k9dIHlalLxokTJ1j51SoAcnNzmfD2AipUqJCvj3l8\nHN7vTuTi4k3kVKlqCE2FQiEpRp2py1g/O3bsGBeuRWFfvw0ffvnDIwE97+bRk7ndbyQJz3QtMy8Z\n67LKSTdkdJLx3AN5vfRBZeoS4u7ZhD7DJxW4zun7tVjGRHB+2bYytlIoFE8DxWbqQUFBeHp6Ur9+\nfRYuXFhovxMnTmBmZsaOHTtKVLA0kal+5j9gEN4+TfjPvPlUMDMvsI9leBgen73LhaVbEBUrlqmf\njHVZ5aQbMjrJdO49jKxe+lBkpq7RaJg2bRp79uzB2dmZli1b4u/vj5eX1yP9Zs2aRa9evRBClKpw\neeXw4UPMXvEjtnb21HJ1f2S9SXY2Pm+OInzah6TV9zaAoUKheBooMlMPCQnBw8MDNzc3zM3NGTFi\nBAEBAY/0++KLLxg6dCjVq1cvNdHSwND1s4CAACytrLC0siI1NYX6jZrh6lQTywLmbqm74hOyqzgQ\nNXaaAUzlrMsqJ92Q0cnQ515hyOqlD0UG9ZiYGFxdXbVtFxcXYmJiHukTEBDA1KlTATApg+F15YW7\nd+/Suc8w/ncijp/PJGNlY1tgP7uTR3De/g2XFq0vk+GLCoXi6aXI8osuAXr69Ol8+umnmJiYIIQo\nsvwyY8YMrK2tAfD19aVdu3baGtaDT8iybj/AEPuvUKECFczMqGRpRXZyLNn3/6l/PsiuKplUotHb\nYzi1YCVpFU15UG1/sP7f/Uur/WBZWe1P1/bDbjL4yNg2r+xY6vvTaDTExsbqfPw/WGbo81/G9v79\n+9m5cyeANl7qg4koIgoHBwczZ84cgoKCAFiwYAGmpqbMmjVL28fd3V0byOPi4rCysuKbb77B398/\n/47+DvqKf1izZg0/7wlm+vw1hfbxfvsFcitW4s95q8rQTKHQnblT/Jnx6qRHznlFyaBv7Cyy/NKi\nRQvCwsKIiIggKyuL7du3P/LG/fXXX4SHhxMeHs7QoUP56quvnpo311D1s5MnTxIQEMDp04/ezOLh\nDNRx5/fYnT7G1dlLy1KvQGSsyyon3ZDRSdbataxe+lBk+cXMzIwVK1bQs2dPNBoNEydOxMvLi1Wr\n8rLGKVOmlIlkeWPYiJFUrVkbKysbOvQZUWCfijej8JwzjTNrd5Jrpf9XMIVCYZwUWX4p0R2p8ouW\nuu4ezFkThLObR8EdcnNpNqYb8c88S0QB0+0qFDKhyi+li76xU11RWkbExMSwcuVXCCFISLhXZN/a\na5dikpNNxEvvlJGdQqEoL6i5X8qIY8eOsfV/P3HrvhXDpryHo1PtAvuZnT+K2+pFXFzyLfx73hcD\nImNdVjnphoxOstauZfXSB5WplyF1PLwKvHvRA0wzM6j75Sdcnb2UTBe3shNTKBTlBqMO6mUxz8N7\nsz/gWHAwsbF3qFHHs8i+9T+diXnFKoQNGFXqXvoi4/whykk3ZHSSdY4VWb30waiDelkQuGsXHQaM\nx6VuA1zqNii0n8MfgVTb+wvHfzujrhpVKBSPjaqplwGevq1p3r47NZzrFLjePC4W7/cmcfGzTWSY\nZJeJk77IWJdVTroho5OstWtZvfTBqIN6aaLRaNBoNMUPRRIC73cmcHPIOBJbdyobOYVCUW4x6qBe\nWvWzEydOYGFhgYWFBZcvXcDatnKhfV22fIVF3B3+em0OIGf9E+T0Uk66IaOTrLVrWb30QdXUS4Hk\n5GSate3Mgk17i+xnHXYJ92UfcfL7IwgLizKyUygU5RmjztRLun4WExNDcHAwly5dKravyf37+Lzx\nPNfeXkD6Qz+gylj/BDm9lJNuyOgka+1aVi99UJl6CTJ+wiTCrodjY1eFZu17FtnXY8lsMlzduTls\nYhnZKRQKY8Cog3pJ1M+ysrLYsWMHOTk5REVH8dKHX9C8ffciH1P1yB5q7NzG8d/OPjJ8Ucb6J8jp\npZx0Q0YnWWvXsnrpg1EH9ZLg/PnzTJn6Mm0696GOZzNc3Yu+wMg84R7eM8dxadEGsu0dyshSoVAY\nC0Yd1B++88qT4OxalxlLNhffUQi83pvMnb4jiG/XrcAuD99dSCZk9FJOuiGjU0mdeyWNrF76YNRB\n/Un46ecA9u7dS2xsLLpOiun0/Voso/7i/H+3lqqbQqEwXow6qD/JJ/KmbzeTbmKDh/czvNBnQrH9\nrcKv4vHZu5z67gCiYsVC+8mWUT1ARi/lpBsyOsmaDcvqpQ9GHdSflFad+9Cpz3PF9jO5fx+f10fw\n1+tzSavvXQZmCoXCWFHj1MuA+gtnkunsRvSoqcX2lXFMMcjppZx0Q0YnWceDy+qlDypTL2Wq/18A\n1fcEcPzX02r2RYVCUeoYdVAv7fpZxZuReM5+kXNf/USOnb1Oj5Gx/glyeikn3ZDRSdbataxe+mDU\nQf1xSEtLIycnh+zsoqfINcnJofH054mc8AZJzZ8pIzuFQmHsqJq6Hty8eRM7OztcXGtz8MB+qjgU\n/qnuvmwOGitrbrw4U699yFj/BDm9lJNuyOgka+1aVi99UJm6HmRkZFDLpQ7r910vsl/VI3tw+mFd\nXh3d1Kg/NxUKRRlj1BGnNOpnFnF38J7xAhc/20RWtRp6P17G+ifI6aWcdENGJ1lr17J66YPK1HXg\n2rVrnDp1itu3bxfdMTeXRm+P5dbgcYVOA6BQKBSliVFn6rrWzz5dtJiP5i3mlz1H6TpgTKH93L5a\nQIX0NP6aPvexnWSsf4KcXspJN2R0krV2LauXPqhMvRByc3NZvnw5aWlpnD51it7DX6TvyBcL7V/1\nyB5cN39JyE8nEGbqZVUoFIbBqDP1oupniYmJzHrnHS7FpOPZuid+zzxbaN+Kt6Jp9NYYLizdwv2a\nzk/kJGP9E+T0Uk66IaOTrLVrWb30QaegHhQUhKenJ/Xr12fhwoWPrN+yZQu+vr40adKEdu3ace7c\nuRIXNQSWllaMf3se49+eh1OdegX2McnKovGrzxE57nUS2nYpY0OFQqHIT7FBXaPRMG3aNIKCgrh0\n6RJbt27l8uXL+fq4u7tz8OBBzp07xwcffMCLLxZeppCJkqif1f90BtlVq+s9Hr0wZKx/gpxeykk3\nZHSStXYtq5c+FFv8DQkJwcPDAzc3NwBGjBhBQEAAXl5e2j5t27bV/r9169ZER0eXvKmE1Ph1G9X+\n+I2Qn0+q8egKhUIKio1EMTExuLq6atsuLi7ExMQU2n/t2rX06dOnZOxKmSepn1ldu0zDj1/l/Iof\ndJ7XRRdkrH+CnF7KSTdkdJK1di2rlz4Um6mb6DGz4B9//MG6des4cuTIE0nJjllyIr4vDSRs1iJS\nGvkZWkehUCi0FBvUnZ2diYqK0rajoqJwcXF5pN+5c+eYPHkyQUFB2NsXnLnOmDEDa2trAHx9fWnX\nrp32k/FBLass2wkJCTRs2LDA9fHx8TRoUF/r/qAuaW7tgM8bo/hrwHNE9+iL+b/X/50VPW77wbKS\n2l5JtTNuX8HMyl4an+zkWHLSE7Cs2VAanwfI9v7926009qfRaPLd37O48+/KlSvY29sb9PwvqP1g\nmSF99u/fz86dOwG08VIfTIQQRd5iMycnh4YNG7J3716cnJxo1aoVW7duzVdTj4yMpGvXrmzevJk2\nbdoUvCMTE4rZVZlT0E1ms7OzuXPnDgkJCXTo2IkfTsXnW19v8bvYnTnO6Q2/I8zNKWlkvEkwyOml\nnHSjtJ3mTvFnxquT8Pf31/kxst7gWUYvfWNnsZm6mZkZK1asoGfPnmg0GiZOnIiXlxerVq0CYMqU\nKXz88cckJCQwdWrenX3Mzc0JCQl5zKdQdhT05n388Sf8d9kyrG1sqduwcb51NX7ZSo2d2zmxI6RU\nAjrIWf8EOb2Uk27I6CRb4HyArF76UGymXmI7kjBTf5jQ0FCSk5P56quvqezWjOFT8g9RtL0Qit/4\nXoR+u4dUzyYGslQo5ONxMnWF7ugbO416HN6DOlZubi4tW7bkrffmcC3qNvW8m+brZxF3hyZTB/Hn\nJ1+VekCXcUwxyOmlnHRDRidZx4PL6qUPapKSvxFCsHDz/keWm2ak4/uiP7eGjie215CyF1MoFAo9\nMOpMvdj6WW4uPm+NIb1uA/567aMycZKx/glyeikn3ZDRSdbataxe+qAy9SKo/+lMzBPiOP/5btBj\nvL5CoVAYCqMO6vv37+fbzd8V+COEy+aVVPvjN0787yiiYsUyc5JxSBzI6aWcdENGJxmHDoK8Xvpg\n1OWX0NBQzodFYefekve/+F673OGPndRd8Qln1uwkp0pVAxoqFAqFfhh1pp6ZmYlHI798N7+ofOY4\njWaO4+yqX8goZLrd0kS2jOoBMnopJ92Q0UnWbFhWL30wyqDer/8AbkRGEnvnNj2H/RPQrcMu4Ttl\nAJcWriepWdsitqBQKBRyYpRB/eCB/cxZ/SuVK1WgRj1fACrF3MBvfC/C3ltCXNd+BnOTsf4Jcnop\nJ92Q0UnW2rWsXvpglEEdoJ6XLxbiPubWNpjHxeI3tjs3Jr3N7QGjDK2mUCgUj43RBHUhxD9XkIpc\nIK/WaJaUgN+EXtzpP5Koca8ZUlHrJCMyeikn3ZDRSdZsWFYvfTCa0S8bN26kjpsbjXyaUMXBEXOL\nipglJdBsbHcS2nThr9fnGFpRoVAonhijCeoZGRn0HDKObcfvsGHfdawyM6jzwQQSWnci7N3PpLm4\nSMZ5OkBOL+WkGzI6yTrHiqxe+mA0Qf1hHmToKZ5NpAroCoVC8aSU+5r6vn37iIqK4tixY4A15vFx\n+I3vRUKrjsROnSNdQJex/glyeikn3ZDRSdbataxe+lDug/rYcePxaNQCS2sberZqRfORHYl71p9r\nMxZIF9AVCoXiSSn3QR1g8ntLqXs/E79xPYkaM43IyW8Dco7fldEJ5PRSTroho5Os48Fl9dIHo6ip\nV718lubPd+av1z7SBnSFQqEoj5TLTP3y5cvM/fg/5ApBxzu36TJzPH8uXMfd7gPy9ZMtewE5nUBO\nL+WkGzI6yZoNy+qlD+UyqJ85c4YLV66zxKkOra0rc2bD76T6NDO0lkKhUJQ65bL8UuH+ff579zZt\nb1zn3M6zhQZ0GcfvyugEcnopJ92Q0UnW8eCyeulDucrUR495gVt//MEXt29y07kOJ7ceINfK2tBa\nCoVCUWaUq0zd8cB+fklKIvH1uWT8eqbYgC5jrVFGJ5DTSznphoxOstauZfXSh6cuU09KSkKj0Wjb\np06dYliPHnwOvAzsXxVAxW7+WBrMUKFQKAzHUxXUz507R7NmzbCxraxd1jk7m6tW1mQOGsu1WYuo\naG2j8/ZkHL8roxPI6aWcdENGJ1nHg8vqpQ9PRVC/c+cON27c4Pz583j5tuDz/wVjHheLx2fv4nD4\n/7i0YA3xHXoYWlOhUCgMzlMR1F+a+gqnzpylsp09jZu1x3X9Muqu/A+3Bo3l2K4LaB7K3PVBtuwF\n5HQCOb2Uk27I6CRrNiyrlz5IF9SvXLnCqVOn8i2LiAhn4tsLGZSrwX3ZR9yv4czJrQdJ9/AykKVC\noVDISbFBPSgoiOnTp6PRaJg0aRKzZs16pM9rr73Grl27sLKyYsOGDfj5+eklkZuby/r168nIyODb\nzVtIvZ+Lc516AFTIzWWoaSWmLplNBWsbwt5dwr1OvUpkMi4Za40yOoGcXspJN2R0krV2LauXPhQ5\npFGj0TBt2jSCgoK4dOkSW7du5fLly/n6BAYGcu3aNcLCwli9ejVTp07VeecnT57kk08+4d133+WV\nadPYG/InTg2a8/biTXwwczErPXz46cRhXjYzJ/KdRZz4KYR7nXuX2OyK504eKZHtlCQyOoGcXspJ\nN2R0OnJEPieQ10sfigzqISEheHh44Obmhrm5OSNGjCAgICBfn19++YUXXngBgNatW5OYmMidO3cK\n3aYQgg8/msPr099g0qTJ/Lz7EDFpFrz8wXLefOld5nk1ZcCHL9OmT2Mso8I5881vnPpuP3HP9i/x\nqXIvnj9botsrCWR0Ajm9lJNuyOh09qx8TiCvlz4UWX6JiYnB1dVV23ZxceH48ePF9omOjqZGjRqP\nbG/0mBfQaDT87/ttvPzWPIa2fJauDjVwvXkD+90/YfHZu8Q/043o0S8T16UvuRUrPenzUygUCqOi\nyKBuomNmLITQ6XEvbd6EDbAcqPzZe9y0tCLMtjI/2VbhQhV7/qztRu79NPhpQ95fKZMQG8Nfl04V\n37EMkdEJ5PRSTrpR2k6Xz4RgavqiXo9JS0srJZsnQ1YvfSgyqDs7OxMVFaVtR0VF4eLiUmSf6Oho\nnJ2dH9lWvXr16HD9+j8LcnMhLTXv7/bNx/UvAU4bcN+FIaMTyOmlnHSjdJ369++v92M+++yzUjB5\ncmTzqlevnl79iwzqLVq0ICwsjIiICJycnNi+fTtbt27N18ff358VK1YwYsQIgoODqVKlSoGll2vX\nruklplAoFAr9KTKom5mZsWLFCnr27IlGo2HixIl4eXmxatUqAKZMmUKfPn0IDAzEw8MDa2tr1q9f\nXybiCoVCoXgUE/HvgrhCoVAonlpKferdoKAgPD09qV+/PgsXLizt3elEVFQUXbp0oVGjRvj4+LB8\n+XJDK2nRaDT4+fk9Vo2yNEhMTGTo0KF4eXnh7e1NcHCwoZVYsGABjRo1onHjxjz//PPcv3/fIB4T\nJkygRo0aNG7cWLssPj6e7t2706BBA3r06EFiYqLBnWbMmIGXlxe+vr4MHjyYpKQkgzs9YMmSJZia\nmhIfHy+F0xdffIGXlxc+Pj4FXmhZ1k4hISG0atUKPz8/WrZsyYkTJ4rfkChFcnJyRL169UR4eLjI\nysoSvr6+4tKlS6W5S524deuWOH36tBBCiJSUFNGgQQMpvIQQYsmSJeL5558X/fv3N7SKEEKIsWPH\nirVr1wohhMjOzhaJiYkG9QkPDxd169YVmZmZQgghhg0bJjZs2GAQl4MHD4rQ0FDh4+OjXTZjxgyx\ncOFCIYQQn376qZg1a5bBnXbv3i00Go0QQohZs2ZJ4SSEEJGRkaJnz57Czc1N3Lt3z+BO+/btE926\ndRNZWVlCCCFiY2MN7tSpUycRFBQkhBAiMDBQdO7cudjtlGqmrsvFS4agZs2aNG3aFAAbGxu8vLy4\neQJYGXsAAAopSURBVNOQI3DyiI6OJjAwkEmTJj0yTNQQJCUlcejQISZMmADk/cZiZ2dnUKfKlStj\nbm5Oeno6OTk5pKenFzjaqizo0KED9vb2+ZY9fDHeCy+8wM8//2xwp+7du2Nqmneqt27dmujoaIM7\nAbz55pssWrSoTF0eUJDTV199xbvvvou5uTkA1atXN7hTrVq1tN+sEhMTdTrWSzWoF3RhUkxMTGnu\nUm8iIiI4ffo0rVu3NrQKb7zxBosXL9aegIYmPDyc6tWrM378eJo1a8bkyZNJT083qFPVqlV56623\nqF27Nk5OTlSpUoVu3boZ1Olh7ty5ox39VaNGjSKvrjYE69ato0+fPobWICAgABcXF5o0aWJoFS1h\nYWEcPHiQNm3a0LlzZ06ePGloJT799FPt8T5jxgwWLFhQ7GNKNXroevGSoUhNTWXo0KEsW7YMGxvd\nb65RGvz22284Ojri5+cnRZYOkJOTQ2hoKC+//DKhoaFYW1vz6aefGtTp+vXr/Pe//yUiIoKbN2+S\nmprKli1bDOpUGCYmJlKdA/PmzcPCwoLnn3/eoB7p6enMnz+fuXPnapfJcMzn5OSQkJBAcHAwixcv\nZtiwYYZWYuLEiSxfvpzIyEg+//xz7bfmoijVoK7LxUuGIjs7myFDhjB69GgGDhxoaB2OHj3KL7/8\nQt26dRk5ciT79u1j7NixBnVycXHBxcWFli1bAjB06FBCQ0MN6nTy5EmeeeYZHBwcMDMzY/DgwRw9\netSgTg9To0YNbt++DcCtW7ekmfFvw4YNBAYGSvEBeP36dSIiIvD19aVu3bpER0fTvHlzYmNjDerl\n4uLC4MGDAWjZsiWmpqbcu3fPoE4hISEMGjQIyDv/QkJCin1MqQb1hy9eysrKYvv27fj7+5fmLnVC\nCMHEiRPx9vZm+vTphtYBYP78+URFRREeHs62bdvo2rUrmzZtMqhTzZo1cXV15erVqwDs2bOHRo0a\nGdTJ09OT4OBgMjIyEEKwZ88evL29Der0MP7+/mzcuBGAjRs3SpEwBAUFsXjxYgICAqhUyfDzKTVu\n3Jg7d+4QHh5OeHg4Li4uhIaGGvwDcODAgezbtw+Aq1evkpWVhYODg0GdPDw8OHDgAAD79u2jQYMG\nxT+oNH7FfZjAwEDRoEEDUa9ePTF//vzS3p1OHDp0SJiYmAhfX1/RtGlT0bRpU7Fr1y5Da2nZv3+/\nNKNfzpw5I1q0aCGaNGkiBg0aZPDRL0IIsXDhQuHt7S18fHzE2LFjtaMVypoRI0aIWrVqCXNzc+Hi\n4iLWrVsn7t27J5599llRv3590b17d5GQkGBQp7Vr1woPDw9Ru3Zt7bE+depUgzhZWFhoX6eHqVu3\nbpmPfinIKSsrS4wePVr4+PiIZs2aiT/++MMgTg8fTydOnBCtWrUSvr6+ok2bNiI0NLTY7aiLjxQK\nhaIcIccwC4VCoVCUCCqoKxQKRTlCBXWFQqEoR6igrlAoFOUIFdQVCoWiHKGCukKhUJQjVFBXGJS+\nffuSnJysc/+IiIgCp3Ata9zc3AqdLrZbt26kpKTotb3s7GyaN29e6Pphw4YRHh6u1zYVxokK6gqD\nsnPnTipXrmxoDb0pbE6Xffv20bBhQ2xtbfXa3uHDh2nfvn2h6ydPnsznn3+u1zYVxokK6opSY/Hi\nxXzxxRdA3gyUzz77LJAX+EaPHg38k/FGRETg5eXFiy++iI+PDz179iQzMxOAU6dO4evrS9OmTVm5\ncmWB+7p16xYdO3bEz8+Pxo0bc+TIESBvauU333wTHx8funXrRlxcHJA3/0jv3r1p0aIFHTt25MqV\nKwDcvXuXoUOH0qpVK1q1aqWdV+bevXv06NEDHx8fJk+eXOgEVN999x0DBgwA8r5VeHp6Mn78eBo2\nbMioUaPYvXs37dq1o0GDBvlueBAUFETv3r1JS0ujb9++NG3alMaNG/P9998D0LlzZwIDAx/znVAY\nFaV96avCeAkODhbPPfecEEKI9u3bi9atW4vs7GwxZ84csXr1aiGE0N4gITw8XJiZmYmzZ88KIfJu\nfrF582YhhBCNGzcWhw4dEkLk3YTi3zdbECLv5iLz5s0TQgih0WhESkqKEEIIExMT8d133wkhhPj4\n44/FtGnThBBCdO3aVYSFhWk9u3btKoQQYuTIkeLw4cNCCCFu3LghvLy8hBBCvPrqq+KTTz4RQgix\nc+dOYWJiUuCl7Z6entrlD57ThQsXRG5urmjevLmYMGGCEEKIgIAAMXDgQO3jWrVqJTIyMsQPP/wg\nJk+erF2elJSk/X/Hjh2luZmLQl6KvPG0QvEkNGvWjFOnTpGSkkKlSpVo0aIFJ0+e5PDhw9oM/mHq\n1q2rnV+7efPmREREkJSURFJSkrY0MWbMGHbt2vXIY1u2bMmECRPIzs5m4MCB+Pr6AmBqasrw4cMB\nGD16NIMHDyYtLY2jR4/y3HPPaR+flZUF5E1advnyZe3ylJQU0tLSOHToED/99BMAffr0KfCmDwA3\nb96katWq+Z7T/7d3/yDphHEcx98ZpRFWBjW4lEMQeJm6RNFTQxEFzS0hBLU1BOHQ0J/BTVxsqYao\npSAMhEiihjiKhiKQanUICWprbCiu3yAe+Usj+RnE/b6v6cTnnrsD+eg99/h98kXQvF6vWftd0zTu\n7++B3LoDzc3NOBwOfD4f4XCYhYUFxsfHC4Zk3G63eUcjRCkS6uLH1NTU4PF42N7epq+vD5/Px+np\nKZlMhs7Ozk/t7Xa7uV1dXc3Ly8unNu8lhj2UUpyfn3N4eMjU1BTz8/OEQqFP+1ZVVWEYBi6Xi3Q6\nXbT/y8tLamtrv33sr3y8JpvNZvZrs9l4e3sDckMvo6OjAHR0dJBOp0mlUiwuLjI0NMTS0pJ5/N+y\ngIr4veQTIn6UUopYLMbg4CBKKdbX1wkGg9/ev7GxkaamJnOMvFQ98Gw2S0tLCzMzM0xPT5uBbRgG\niUQCyI13K6VwOp14PB729/eBXFje3t4CMDIyUrAQ+c3NDQADAwPs7u4CcHR0xPPzc9HzcLvdZdfg\nPj4+ZmxsDMg9G3A4HExOThIOhwvq1z8+PtLW1lZW3+L/I6EufpRSiqenJ3p7e2ltbaWurg6llPn+\nx1kkf88oyb/e2tpidnaWQCBQtB2Aruv4/X6CwSCJRIK5uTkA6uvrubq6oqurC13XWV5eBnJfDpub\nm/j9fjRN4+DgAIDV1VWur6/p7u7G6/WysbEBwMrKCmdnZ2iaRjKZLBmu/f39Bcuglbqm/LZhGGQy\nGbNO9t3dHT09PQQCASKRiPkr/fX1lYeHh6J3OEJ8JKV3haU5nc6y54z/C13X2dvbY21t7VvtLy4u\n2NnZKTmrJ+/k5IRUKkU8Hq/EaQoLk1AXltbQ0FDWn5sqYXh4mGQyWfZc9a9MTEwQjUZpb2+vWJ/C\nmiTUhRDCQmRMXQghLERCXQghLERCXQghLERCXQghLERCXQghLERCXQghLOQP3c9uNsnRvykAAAAA\nSUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x9af1cd0>"
]
}
],
"prompt_number": 313
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"1) Logit transform by hand"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Logit transform (inverse sigmoid)\n",
"\n",
"maps $[0,1] \\mapsto [-\\infty, +\\infty]$\n",
"\n",
"$$f(p) = log(\\frac{p}{1-p}) = log(p) - log(1-p) $$"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def logit(p):\n",
" return np.log10(p/(1-p))\n",
"logit(np.array([0.01, 0.1, 0.5, 0.9, 0.99]))"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 70,
"text": [
"array([-1.99563519, -0.95424251, 0. , 0.95424251, 1.99563519])"
]
}
],
"prompt_number": 70
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"hist, bin_edges= np.histogram(vel_samp, bins=100, density=True)\n",
"cumhist = hist.cumsum()*(bin_edges[1]-bin_edges[0])"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 306
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"plt.plot(bin_edges[:-1], logit(cumhist))\n",
"plt.plot(vel, logit(weib.cdf(vel)), 'r')\n",
"plt.title('Weibull logit cdf, scale={:.2f}, shape={:.2f}'.format(w_scale, w_shape))\n",
"plt.ylim(-4,4);\n",
"plt.xlabel('wind speed (m/s)');\n",
"plt.ylabel('log-odds')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 307,
"text": [
"<matplotlib.text.Text at 0x96f07d0>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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dRdWVn5BatSxuw17Q00DIMpDiOmkjECKHio6G77/Xg8MOHoSwML3oV/Xq1x+w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\nEHmcFARCCJHH/T95zUoz18gKDAAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x96ee290>"
]
}
],
"prompt_number": 307
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"2) Logit transform as a Matplotlib scale transform"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from matplotlib import scale as mscale\n",
"from matplotlib import transforms as mtransforms\n",
"from matplotlib import ticker as mticker\n",
"from numpy import ma\n",
"\n",
"class ProbaFormatter(Formatter):\n",
" '''Probability formatter (using Math text)'''\n",
" def __call__(self, x, pos=None):\n",
" s = ''\n",
" if 0.01 <= x <= 0.99:\n",
" if x in [.01, 0.1, 0.5, 0.9, 0.99]:\n",
" s = '{:.2f}'.format(x)\n",
" elif x < 0.01:\n",
" if mticker.is_decade(x):\n",
" s = '$10^{%.0f}$' % np.log10(x)\n",
" elif x > 0.99:\n",
" if mticker.is_decade(1-x):\n",
" s = '$1-10^{%.0f}$' % np.log10(1-x)\n",
" return s\n",
"\n",
" def format_data_short(self, value):\n",
" 'return a short formatted string representation of a number'\n",
" return '%-12g' % value\n",
"\n",
"class LogitScale(mscale.ScaleBase):\n",
" \"\"\"\n",
" Scales data in range 0,1 to -infty, +infty\n",
" \"\"\"\n",
"\n",
" # The scale class must have a member ``name`` that defines the\n",
" # string used to select the scale.\n",
" name = 'logit'\n",
"\n",
" def __init__(self, axis, **kwargs):\n",
" \"\"\"\n",
" Any keyword arguments passed to ``set_xscale`` and\n",
" ``set_yscale`` will be passed along to the scale's\n",
" constructor.\n",
"\n",
" thresh: The degree above which to crop the data.\n",
" \"\"\"\n",
" mscale.ScaleBase.__init__(self)\n",
" p_min = kwargs.pop(\"p_min\", 1e-2)\n",
" if not (0 <p_min < 0.5):\n",
" raise ValueError(\"p_min must be between 0 and 0.5 excluded\")\n",
" p_max = kwargs.pop(\"p_max\", 1-p_min)\n",
" if not (0.5 < p_max < 1):\n",
" raise ValueError(\"p_max must be between 0.5 and 1 excluded\")\n",
" self.p_min = p_min\n",
" self.p_max = p_max\n",
"\n",
" def get_transform(self):\n",
" \"\"\"\n",
" Override this method to return a new instance that does the\n",
" actual transformation of the data.\n",
" \"\"\"\n",
" return self.LogitTransform(self.p_min, self.p_max)\n",
"\n",
" def set_default_locators_and_formatters(self, axis): \n",
" expon_major = np.arange(1, 18)\n",
" # ..., 0.01, 0.1, 0.5, 0.9, 0.99, ...\n",
" axis.set_major_locator(mticker.FixedLocator(\n",
" list(1/10.**(expon)) + \\\n",
" [0.5] + \\\n",
" list(1-1/10.**(expon))\n",
" ))\n",
" minor_ticks = [0.2,0.3,0.4,0.6,0.7, 0.8]\n",
" for i in range(2,17):\n",
" minor_ticks.extend(1/10.**i * np.arange(2,10))\n",
" minor_ticks.extend(1-1/10.**i * np.arange(2,10)) \n",
" axis.set_minor_locator(mticker.FixedLocator(minor_ticks))\n",
" axis.set_major_formatter(ProbaFormatter())\n",
" axis.set_minor_formatter(ProbaFormatter())\n",
"\n",
" def limit_range_for_scale(self, vmin, vmax, minpos):\n",
" return max(vmin, self.p_min), min(vmax, self.p_max)\n",
"\n",
" class LogitTransform(mtransforms.Transform):\n",
" input_dims = 1\n",
" output_dims = 1\n",
" is_separable = True\n",
"\n",
" def __init__(self, p_min, p_max):\n",
" mtransforms.Transform.__init__(self)\n",
" self.p_min = p_min\n",
" self.p_max = p_max\n",
"\n",
" def transform_non_affine(self, a):\n",
" \"\"\"logit transform (base 10)\"\"\"\n",
" p_over = a > self.p_max\n",
" p_under = a < self.p_min\n",
" # saturate extreme values:\n",
" a_sat = np.where(p_over, self.p_max, a)\n",
" a_sat = np.where(p_under, self.p_min, a_sat)\n",
" return np.log10(a_sat / (1-a_sat))\n",
"\n",
" def inverted(self):\n",
" return LogitScale.InvertedLogitTransform(self.p_min, self.p_max)\n",
"\n",
" class InvertedLogitTransform(mtransforms.Transform):\n",
" input_dims = 1\n",
" output_dims = 1\n",
" is_separable = True\n",
"\n",
" def __init__(self, p_min, p_max):\n",
" mtransforms.Transform.__init__(self)\n",
" self.p_min = p_min\n",
" self.p_max = p_max\n",
"\n",
" def transform_non_affine(self, a):\n",
" \"\"\"sigmoid transform (base 10)\"\"\"\n",
" return 1/(1+10**(-a))\n",
"\n",
" def inverted(self):\n",
" return LogitScale.LogitTransform(self.p_min, self.p_max)\n",
"\n",
"mscale.register_scale(LogitScale)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 308
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%matplotlib inline"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 309
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fig = plt.figure(figsize=(10,8))\n",
"ax = plt.subplot(111)\n",
"plt.plot(vel, weib.cdf(vel), 'r')\n",
"plt.hist(vel_samp, bins = 100, cumulative=True, **h_opts)\n",
"\n",
"ax.set_yscale('logit', p_min=1e-4) \n",
"ax.set_ylim(1e-4, 0.9999);\n",
"plt.title('Weibull cdf, scale={:.2f}, shape={:.2f}'.format(w_scale, w_shape))\n",
"plt.xlabel('wind speed (m/s)');"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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hMjKSbt265Tm3YsWKeHt74+/vz3PPPcecOXOMjZxJkyYREhJCs2bN8PLyol27dkV+0nHe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\n",
"text": [
"<matplotlib.figure.Figure at 0x93cc050>"
]
}
],
"prompt_number": 314
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"n_loc = 5.3\n",
"n_scale = 2\n",
"norm = stats.norm(loc=n_loc, scale=n_scale)\n",
"\n",
"vel_samp2 = norm.rvs(N_samp)\n",
"vel_samp2[vel_samp2<0] = 0\n",
"vel_samp2.mean()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 332,
"text": [
"5.0765252605208939"
]
}
],
"prompt_number": 332
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"plt.hist(vel_samp2, bins = 15, cumulative=False, **h_opts)\n",
"plt.plot(vel, norm.pdf(vel), 'r')\n",
"plt.title('Normal cdf, loc={:.2f}, scale={:.2f}'.format(n_loc, n_scale))\n",
"plt.xlabel('wind speed (m/s)');"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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Zz76I3O2R/X2XLtC6UxBbd8STVb5CEaUzRq4je4B582DVKstFWYQQuuitnaVn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\nDJBiL4QQZcD/A0KGTejKPpZWAAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0xa506ad0>"
]
}
],
"prompt_number": 333
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fig = plt.figure(figsize=(10,8))\n",
"ax = plt.subplot(111)\n",
"plt.plot(vel, norm.cdf(vel), 'r')\n",
"plt.plot(vel, weib.cdf(vel), color='orange')\n",
"plt.hist(vel_samp2, bins = 200, cumulative=True, **h_opts)\n",
"\n",
"ax.set_yscale('logit', p_min=1e-4)\n",
"plt.title('Normal cdf, loc={:.2f}, scale={:.2f}'.format(n_loc, n_scale))\n",
"plt.xlabel('wind speed (m/s)');"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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u34aBA2HmTHjkEaNeSlV5m5Cq8k49B+GjITcLntgHbsbbqkpVeaucjJQJIYTW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\nhRBCmJAUZSqn1bl4S8770qVLREdHM3HiJHLy8nC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Mnz8fgDvueYTwW3tzcxg0bVl2wtia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4AAAK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\nEEIYgBRlQgghhBAGIEWZEEIIIYQB/D9AJFZRB1SdegAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0xa5cc910>"
]
}
],
"prompt_number": 342
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
}
],
"metadata": {}
}
]
}
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